Online fraud detection employs various technologies to identify and mitigate fraudulent activities. Key techniques include machine learning, which analyzes patterns in transactional data to detect anomalies. AI algorithms can adapt and improve over time, enhancing their ability to spot new fraud tactics. Additionally, biometric authentication, such as fingerprint or facial recognition, adds layers of security. Behavioral analytics examines user behavior to flag suspicious actions, while real-time monitoring systems alert stakeholders to potential fraud as it occurs. Together, these technologies create robust defenses against online threats.